research-article

Efficient and generic evaluation of ranked queries

Authors:

Jignesh M. PatelAuthors Info & Claims

SIGMOD '11: Proceedings of the 2011 ACM SIGMOD International Conference on Management of data

Pages 601 - 612

https://doi.org/10.1145/1989323.1989386

Published: 12 June 2011 Publication History

Abstract

An important feature of the existing methods for ranked top-k processing is to avoid searching all the objects in the underlying dataset, and limiting the number of random accesses to the data. However, the performance of these methods degrades rapidly as the number of random accesses increases. In this paper, we propose a novel and general sequential access scheme for top-k query evaluation, which outperforms existing methods. We extend this scheme to efficiently answer top-k queries in subspace and on dynamic data. We also study the "dual" form of top-k queries called "ranking" queries, which returns the rank of a specified record/object, and propose an exact as well as two approximate solutions. An extensive empirical evaluation validates the robustness and efficiency of our techniques.

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Cited By

Jiang TZhang BLin DGao YLi Q(2022)Efficient parallel processing of high-dimensional spatial kNN queriesSoft Computing10.1007/s00500-022-07081-026:22(12291-12316)Online publication date: 2-May-2022
https://doi.org/10.1007/s00500-022-07081-0
Li YWang JPullman BBandeira NPapakonstantinou Y(2020)Index-based, High-dimensional, Cosine Threshold Querying with Optimality GuaranteesTheory of Computing Systems10.1007/s00224-020-10009-6Online publication date: 26-Oct-2020
https://doi.org/10.1007/s00224-020-10009-6
Qin YGuzun G(2019)Multidimensional Preference Query Optimization on Infrastructure Monitoring Systems2019 IEEE International Conference on Big Data (Big Data)10.1109/BigData47090.2019.9005666(3727-3736)Online publication date: Dec-2019
https://doi.org/10.1109/BigData47090.2019.9005666
Show More Cited By

Index Terms

Efficient and generic evaluation of ranked queries
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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Published In

cover image ACM Conferences

SIGMOD '11: Proceedings of the 2011 ACM SIGMOD International Conference on Management of data

June 2011

1364 pages

ISBN:9781450306614

DOI:10.1145/1989323

General Chair:
Timos Sellis
IMIS/RC Athena
,
Program Chair:
Renée J. Miller
University of Toronto
,
Publications Chairs:
Anastasios Kementsietsidis
IBM T.J. Watson Research Center
,
Yannis Velegrakis
University of Trento

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2011

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Author Tag

ranked queries

Qualifiers

Research-article

Conference

SIGMOD/PODS '11

Sponsor:

SIGMOD

SIGMOD/PODS '11: International Conference on Management of Data

June 12 - 16, 2011

Athens, Greece

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Citations

Cited By

Jiang TZhang BLin DGao YLi Q(2022)Efficient parallel processing of high-dimensional spatial kNN queriesSoft Computing10.1007/s00500-022-07081-026:22(12291-12316)Online publication date: 2-May-2022
https://doi.org/10.1007/s00500-022-07081-0
Li YWang JPullman BBandeira NPapakonstantinou Y(2020)Index-based, High-dimensional, Cosine Threshold Querying with Optimality GuaranteesTheory of Computing Systems10.1007/s00224-020-10009-6Online publication date: 26-Oct-2020
https://doi.org/10.1007/s00224-020-10009-6
Qin YGuzun G(2019)Multidimensional Preference Query Optimization on Infrastructure Monitoring Systems2019 IEEE International Conference on Big Data (Big Data)10.1109/BigData47090.2019.9005666(3727-3736)Online publication date: Dec-2019
https://doi.org/10.1109/BigData47090.2019.9005666
Heo JCho JWhang K(2019)Subspace top-k query processing using the hybrid-layer index with a tight boundData & Knowledge Engineering10.1016/j.datak.2012.07.00183(1-19)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1016/j.datak.2012.07.001
Zhu LLiu FMeng WMa QWang YYuan F(2016)Evaluating Top-N queries in n-dimensional normed spacesInformation Sciences: an International Journal10.1016/j.ins.2016.09.035374:C(255-275)Online publication date: 20-Dec-2016
https://dl.acm.org/doi/10.1016/j.ins.2016.09.035
Zhu LMa QMeng WYang MYuan F(2015)An Experimental Evaluation of Aggregation Algorithms for Processing Top-K Queries2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing10.1109/CIT/IUCC/DASC/PICOM.2015.47(326-333)Online publication date: Oct-2015
https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.47
Deng TFan W(2014)On the Complexity of Query Result DiversificationACM Transactions on Database Systems10.1145/260213639:2(1-46)Online publication date: 26-May-2014
https://dl.acm.org/doi/10.1145/2602136
Guzun GTosado JCanahuate G(2014)Slicing the Dimensionality: Top-k Query Processing for High-Dimensional SpacesTransactions on Large-Scale Data- and Knowledge-Centered Systems XIV10.1007/978-3-662-45714-6_2(26-50)Online publication date: 21-Nov-2014
https://doi.org/10.1007/978-3-662-45714-6_2
Lu JSenellart PLin CDu XWang SChen XCandan KChen YSnodgrass RGravano LFuxman A(2012)Optimal top-k generation of attribute combinations based on ranked listsProceedings of the 2012 ACM SIGMOD International Conference on Management of Data10.1145/2213836.2213883(409-420)Online publication date: 20-May-2012
https://dl.acm.org/doi/10.1145/2213836.2213883

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